Faculty Opinions recommendation of Real-world Effectiveness of Sofosbuvir/Velpatasvir for Treatment of Chronic Hepatitis C in British Columbia, Canada: A Population-Based Cohort Study.
Notice bibliographique
Résumé
Background.Clinical trials show high efficacy of sofosbuvir/velpatasvir (SOF/VEL), but there are limited data from "realworld" settings.We aimed to evaluate SOF/VEL effectiveness for all hepatitis C virus (HCV) genotypes (GTs) in British Columbia (BC), Canada. Methods.We used the BC Hepatitis Testers Cohort, which includes all HCV cases in the province linked to administrative databases, including prescriptions to end of 2018.We measured sustained virologic response (SVR; negative RNA ≥10 weeks after treatment end) and identified characteristics associated with non-SVR.Conservatively, we excluded individuals with no assessment for SVR if their last RNA test after treatment initiation was negative (but included if positive).Results.Of 2821 eligible participants, most were infected with GT1 (1076, 38.1%) or GT3 (1072, 38.0%), and a minority (278, 9.9%) were treated with RBV.SVR was 94.6% (2670/2821) overall and 94.5% (1017/1076) for GT1, 96.4% (512/531) for GT2, and 93.7% (1004/1072) for GT3.When disaggregated by GT, treatment regimen, and cirrhosis/treatment experience, SVR was lowest (30/40, 75.0%) among treatment-experienced GT3 individuals treated with RBV.Characteristics associated with non-SVR in multivariable analysis included younger age, RBV addition, and being a person with HIV (PWH) or who injects/injected drugs (PWID).When treatment regimen (±RBV) was removed from multivariable model, treatment experience was associated with non-SVR for GT3.Of 151 non-SVR individuals, 56.3% were nonvirological failures (treatment incomplete/no assessment for SVR) and 43.7% were virological failures (nonresponse/relapse).A disproportionately high percentage of non-SVR among PWID was due to nonvirological failure.Conclusions.SOF/VEL was highly effective in this "real-world" population-based cohort.Additional support is required for PWID/PWH to reach SVR. Keywords. hepatitis C; treatment effectiveness; observational study; administrative data; sofosbuvir; velpatasvir; ribavirin.Hepatitis C virus (HCV) and its associated morbidity and mortality are a significant public health issue in Canada and globally [1, 2].In the absence of effective treatment, about 75% of individuals infected with HCV advance to chronic infection, and 10%-15% of chronically infected individuals develop liver cirrhosis within 20 years [3].People with cirrhosis are at higher risk of end-stage liver disease and death.Second-generation oral direct-acting antivirals (DAAs) are short course (8-24 weeks), have fewer adverse effects, and can cure >95% of people with HCV.This high cure rate and ease of use led the World Health Organization to issue the first Global Health Sector Strategy on Viral Hepatitis, with the aim of eliminating HCV as a major public health issue by 2030 [4].Sofosbuvir/velpatasvir (SOF/VEL) is the first of these DAAs to be pan-genotypic and require a single pill taken once daily.SOF/VEL clinical trials published in 2015 demonstrated sustained virologic response (SVR) rates exceeding 97% for all genotypes (GTs) except for GT3 (94.7%) [5-10].In 2016, SOF/ VEL was approved by regulatory agencies in the United States (Food and Drug Administration), Canada (Health Canada), and the European Union (European Commission) [11, 12].
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,022 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,002 |
| Bibliométrie | 0,003 | 0,007 |
| Études des sciences et des technologies | 0,002 | 0,000 |
| Communication savante | 0,003 | 0,001 |
| Science ouverte | 0,004 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,041 | 0,014 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».